Cloud AutoML V1beta1 API - Class Google::Cloud::AutoML::V1beta1::ModelEvaluation (v0.13.0)

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Reference documentation and code samples for the Cloud AutoML V1beta1 API class Google::Cloud::AutoML::V1beta1::ModelEvaluation.

Evaluation results of a model.

Inherits

• Object

Extended By

• Google::Protobuf::MessageExts::ClassMethods

Includes

• Google::Protobuf::MessageExts

Methods

#annotation_spec_id

def annotation_spec_id() -> ::String

Returns

• (::String) — Output only. The ID of the annotation spec that the model evaluation applies to. The The ID is empty for the overall model evaluation. For Tables annotation specs in the dataset do not exist and this ID is always not set, but for CLASSIFICATION

  [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] the display_name field is used.

#annotation_spec_id=

def annotation_spec_id=(value) -> ::String

Parameter

• value (::String) — Output only. The ID of the annotation spec that the model evaluation applies to. The The ID is empty for the overall model evaluation. For Tables annotation specs in the dataset do not exist and this ID is always not set, but for CLASSIFICATION

  [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] the display_name field is used.

Returns

• (::String) — Output only. The ID of the annotation spec that the model evaluation applies to. The The ID is empty for the overall model evaluation. For Tables annotation specs in the dataset do not exist and this ID is always not set, but for CLASSIFICATION

  [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] the display_name field is used.

#classification_evaluation_metrics

def classification_evaluation_metrics() -> ::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics

Returns

• (::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics) — Model evaluation metrics for image, text, video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType.

  Note: The following fields are mutually exclusive: classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#classification_evaluation_metrics=

def classification_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics

Parameter

• value (::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics) — Model evaluation metrics for image, text, video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType.

  Note: The following fields are mutually exclusive: classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns

• (::Google::Cloud::AutoML::V1beta1::ClassificationEvaluationMetrics) — Model evaluation metrics for image, text, video and tables classification. Tables problem is considered a classification when the target column is CATEGORY DataType.

  Note: The following fields are mutually exclusive: classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#create_time

def create_time() -> ::Google::Protobuf::Timestamp

Returns

• (::Google::Protobuf::Timestamp) — Output only. Timestamp when this model evaluation was created.

#create_time=

def create_time=(value) -> ::Google::Protobuf::Timestamp

Parameter

• value (::Google::Protobuf::Timestamp) — Output only. Timestamp when this model evaluation was created.

Returns

• (::Google::Protobuf::Timestamp) — Output only. Timestamp when this model evaluation was created.

#display_name

def display_name() -> ::String

Returns

• (::String) — Output only. The value of display_name at the moment when the model was trained. Because this field returns a value at model training time, for different models trained from the same dataset, the values may differ, since display names could had been changed between the two model's trainings. For Tables CLASSIFICATION

  [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] distinct values of the target column at the moment of the model evaluation are populated here. The display_name is empty for the overall model evaluation.

#display_name=

def display_name=(value) -> ::String

Parameter

• value (::String) — Output only. The value of display_name at the moment when the model was trained. Because this field returns a value at model training time, for different models trained from the same dataset, the values may differ, since display names could had been changed between the two model's trainings. For Tables CLASSIFICATION

  [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] distinct values of the target column at the moment of the model evaluation are populated here. The display_name is empty for the overall model evaluation.

Returns

• (::String) — Output only. The value of display_name at the moment when the model was trained. Because this field returns a value at model training time, for different models trained from the same dataset, the values may differ, since display names could had been changed between the two model's trainings. For Tables CLASSIFICATION

  [prediction_type-s][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type] distinct values of the target column at the moment of the model evaluation are populated here. The display_name is empty for the overall model evaluation.

#evaluated_example_count

def evaluated_example_count() -> ::Integer

Returns

• (::Integer) — Output only. The number of examples used for model evaluation, i.e. for which ground truth from time of model creation is compared against the predicted annotations created by the model. For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is the total number of all examples used for evaluation. Otherwise, this is the count of examples that according to the ground truth were annotated by the

  annotation_spec_id.

#evaluated_example_count=

def evaluated_example_count=(value) -> ::Integer

Parameter

• value (::Integer) — Output only. The number of examples used for model evaluation, i.e. for which ground truth from time of model creation is compared against the predicted annotations created by the model. For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is the total number of all examples used for evaluation. Otherwise, this is the count of examples that according to the ground truth were annotated by the

  annotation_spec_id.

Returns

• (::Integer) — Output only. The number of examples used for model evaluation, i.e. for which ground truth from time of model creation is compared against the predicted annotations created by the model. For overall ModelEvaluation (i.e. with annotation_spec_id not set) this is the total number of all examples used for evaluation. Otherwise, this is the count of examples that according to the ground truth were annotated by the

  annotation_spec_id.

#image_object_detection_evaluation_metrics

def image_object_detection_evaluation_metrics() -> ::Google::Cloud::AutoML::V1beta1::ImageObjectDetectionEvaluationMetrics

Returns

• (::Google::Cloud::AutoML::V1beta1::ImageObjectDetectionEvaluationMetrics) — Model evaluation metrics for image object detection.

  Note: The following fields are mutually exclusive: image_object_detection_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#image_object_detection_evaluation_metrics=

def image_object_detection_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1beta1::ImageObjectDetectionEvaluationMetrics

Parameter

• value (::Google::Cloud::AutoML::V1beta1::ImageObjectDetectionEvaluationMetrics) — Model evaluation metrics for image object detection.

  Note: The following fields are mutually exclusive: image_object_detection_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns

• (::Google::Cloud::AutoML::V1beta1::ImageObjectDetectionEvaluationMetrics) — Model evaluation metrics for image object detection.

  Note: The following fields are mutually exclusive: image_object_detection_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#name

def name() -> ::String

Returns

• (::String) — Output only. Resource name of the model evaluation. Format:

  projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}

#name=

def name=(value) -> ::String

Parameter

• value (::String) — Output only. Resource name of the model evaluation. Format:

  projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}

Returns

• (::String) — Output only. Resource name of the model evaluation. Format:

  projects/{project_id}/locations/{location_id}/models/{model_id}/modelEvaluations/{model_evaluation_id}

#regression_evaluation_metrics

def regression_evaluation_metrics() -> ::Google::Cloud::AutoML::V1beta1::RegressionEvaluationMetrics

Returns

• (::Google::Cloud::AutoML::V1beta1::RegressionEvaluationMetrics) — Model evaluation metrics for Tables regression. Tables problem is considered a regression when the target column has FLOAT64 DataType.

  Note: The following fields are mutually exclusive: regression_evaluation_metrics, classification_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#regression_evaluation_metrics=

def regression_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1beta1::RegressionEvaluationMetrics

Parameter

• value (::Google::Cloud::AutoML::V1beta1::RegressionEvaluationMetrics) — Model evaluation metrics for Tables regression. Tables problem is considered a regression when the target column has FLOAT64 DataType.

  Note: The following fields are mutually exclusive: regression_evaluation_metrics, classification_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns

• (::Google::Cloud::AutoML::V1beta1::RegressionEvaluationMetrics) — Model evaluation metrics for Tables regression. Tables problem is considered a regression when the target column has FLOAT64 DataType.

  Note: The following fields are mutually exclusive: regression_evaluation_metrics, classification_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#text_extraction_evaluation_metrics

def text_extraction_evaluation_metrics() -> ::Google::Cloud::AutoML::V1beta1::TextExtractionEvaluationMetrics

Returns

• (::Google::Cloud::AutoML::V1beta1::TextExtractionEvaluationMetrics) — Evaluation metrics for text extraction models.

  Note: The following fields are mutually exclusive: text_extraction_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#text_extraction_evaluation_metrics=

def text_extraction_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1beta1::TextExtractionEvaluationMetrics

Parameter

• value (::Google::Cloud::AutoML::V1beta1::TextExtractionEvaluationMetrics) — Evaluation metrics for text extraction models.

  Note: The following fields are mutually exclusive: text_extraction_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns

• (::Google::Cloud::AutoML::V1beta1::TextExtractionEvaluationMetrics) — Evaluation metrics for text extraction models.

  Note: The following fields are mutually exclusive: text_extraction_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#text_sentiment_evaluation_metrics

def text_sentiment_evaluation_metrics() -> ::Google::Cloud::AutoML::V1beta1::TextSentimentEvaluationMetrics

Returns

• (::Google::Cloud::AutoML::V1beta1::TextSentimentEvaluationMetrics) — Evaluation metrics for text sentiment models.

  Note: The following fields are mutually exclusive: text_sentiment_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#text_sentiment_evaluation_metrics=

def text_sentiment_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1beta1::TextSentimentEvaluationMetrics

Parameter

• value (::Google::Cloud::AutoML::V1beta1::TextSentimentEvaluationMetrics) — Evaluation metrics for text sentiment models.

  Note: The following fields are mutually exclusive: text_sentiment_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns

• (::Google::Cloud::AutoML::V1beta1::TextSentimentEvaluationMetrics) — Evaluation metrics for text sentiment models.

  Note: The following fields are mutually exclusive: text_sentiment_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#translation_evaluation_metrics

def translation_evaluation_metrics() -> ::Google::Cloud::AutoML::V1beta1::TranslationEvaluationMetrics

Returns

• (::Google::Cloud::AutoML::V1beta1::TranslationEvaluationMetrics) — Model evaluation metrics for translation.

  Note: The following fields are mutually exclusive: translation_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#translation_evaluation_metrics=

def translation_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1beta1::TranslationEvaluationMetrics

Parameter

• value (::Google::Cloud::AutoML::V1beta1::TranslationEvaluationMetrics) — Model evaluation metrics for translation.

  Note: The following fields are mutually exclusive: translation_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns

• (::Google::Cloud::AutoML::V1beta1::TranslationEvaluationMetrics) — Model evaluation metrics for translation.

  Note: The following fields are mutually exclusive: translation_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, image_object_detection_evaluation_metrics, video_object_tracking_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#video_object_tracking_evaluation_metrics

def video_object_tracking_evaluation_metrics() -> ::Google::Cloud::AutoML::V1beta1::VideoObjectTrackingEvaluationMetrics

Returns

• (::Google::Cloud::AutoML::V1beta1::VideoObjectTrackingEvaluationMetrics) — Model evaluation metrics for video object tracking.

  Note: The following fields are mutually exclusive: video_object_tracking_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

#video_object_tracking_evaluation_metrics=

def video_object_tracking_evaluation_metrics=(value) -> ::Google::Cloud::AutoML::V1beta1::VideoObjectTrackingEvaluationMetrics

Parameter

• value (::Google::Cloud::AutoML::V1beta1::VideoObjectTrackingEvaluationMetrics) — Model evaluation metrics for video object tracking.

  Note: The following fields are mutually exclusive: video_object_tracking_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.

Returns

• (::Google::Cloud::AutoML::V1beta1::VideoObjectTrackingEvaluationMetrics) — Model evaluation metrics for video object tracking.

  Note: The following fields are mutually exclusive: video_object_tracking_evaluation_metrics, classification_evaluation_metrics, regression_evaluation_metrics, translation_evaluation_metrics, image_object_detection_evaluation_metrics, text_sentiment_evaluation_metrics, text_extraction_evaluation_metrics. If a field in that set is populated, all other fields in the set will automatically be cleared.